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Derivative free Kalman filtering used for orchard navigation

机译:用于果园导航的衍生免费卡尔曼滤波

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In this paper the use of derivative free filters for mobile robot localisation is investigated. Three different filters are tested on real life data from an autonomous tractor running in an orchard environment. The localisation algorithm fuses odometry and gyro measurements with line features representing the surrounding fruit trees. The line features are created on basis of 2D laser scanner data by a least square algorithm. The Matlab@ toolbox Kalmtool is used for easy switching between different filter implementations without the need for changing the base structure of the system.
机译:在本文中,研究了用于移动机器人定位的衍生自由滤波器。在果园环境中运行的自主拖拉机的现实生活数据上测试了三种不同的过滤器。本地化算法熔化机器术和陀螺仪测量,具有代表周围果树的线特征。通过最小二乘算法基于2D激光扫描仪数据创建线特征。 MATLAB @ Toolbox Kalmtool用于在不同的过滤器实现之间轻松切换,而无需更改系统的基础结构。

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